Staff Data Engineer

We're looking for a Staff Data Engineer with deep Snowflake expertise and a strong background in complex data modeling in large enterprise environments. This person will work directly with our Data Architect to implement platform standards and deliver against our data platform roadmap — so we need someone who is technically opinionated, able to execute and move a lot of dirt, comfortable setting patterns and standards for others, and ready to operate as a senior technical partner rather than just an individual contributor. KEY RESPONSIBILITIES Possesses relevant data, analytics, and BI engineering experience Strong experience working in Snowflake, Azure Data Factory and Data Modeling Strong command of best practices applied in relational databases and SQL as well as Extract, Transform, and Load (ETL) data into a relational database. Solid understanding of Data Warehousing, Data Lakes, Data Pipelines, and Business Intelligence Applications. Ability to interpret moderately complex data, analytics, and BI requirements and apply data, analytics, and BI design methodologies. Ability to learn new techniques and troubleshooting code without support, in other words, be able to learn on the job. Use APIs to push and pull data from various data systems and platforms. Ability to write clear code that is well-documented and stored in a version control system. Proficient with Python, databases, and SQL expertise. Proven ability to work both independently and collaboratively within a team environment while following established procedures. Excellent listening, interpersonal, communication and problem-solving skills. IDEAL CANDIDATE PROFILE Deep, hands-on Snowflake experience (modeling, performance tuning, advanced features) Experience delivering complex data models in a large enterprise environment Strong command of standard data engineering patterns (dimensional modeling, data vault, medallion architecture, or equivalent) Ability to do meaningful code and design reviews and raise team-wide quality Coalesce, or similar transformation tooling a plus Azure or Microsoft Fabric familiarity helpful given our current stack #J-18808-Ljbffr